University of Cambridge > Talks.cam > Cambridge Networks and Communications meeting > Large-system analysis of multiuser detection with an unknown number of users.

  Browse A-Z

Log in

Googledetails Microsoftdetails

🔐 Log In

Information on

Subscribing to talksdetails Finding a talkdetails Adding a talkdetails Disseminating talksdetails Help and Documentationdetails

ℹī¸ Information

Large-system analysis of multiuser detection with an unknown number of users.

Download to your calendar using vCal

  • UserAdria Tauste Campo (Department of Engineering)
  • ClockMonday 21 July 2008, 16:00-16:30
  • HouseMR3, CMS.

If you have a question about this talk, please contact James Cruise .

Session 4, Cambridge Networks and Communication Meeting

We study multiuser detection where the number of users accessing the channel is unknown by the receiver. In this environment user’s activity must be estimated together with other parameters such as data, power, location, etc. In this paper, we are interested in the performance of such systems when the number of potential users is large. Under some technical assumptions, statistical-physics methodologies can be used for the purpose of determining the macroscopic performance measures of the detector (e.g., multiuser and spectral efficiency). An expansion of the minimum mean-squared error for large signal-to-noise ratio for the joint estimation of user’s activity and their data allows us to analyze asymptotically the user-and-data MAP detector in terms of multiuser efficiency and maximum system load for different quality demands.

This talk is part of the Cambridge Networks and Communications meeting series.

This talk is included in these lists:

Note that ex-directory lists are not shown.

Other lists

Webinar & LT2, Computer Laboratory, William Gates Building. BAS Seminar Room 330b Larmor Society Talks

Other talks

Group Work Discussion II Content, Caching and Kubernetes: Performance and User Experience in the Browser Title to be confirmed Online Causal Inference Seminar Title TBC
 

Š 2006-2025 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity